How You Can Identify Buying Preferences of Customers Using Data Mining Techniques

In a bid to reach new moms on time, Target knows when you’ll get pregnant. Microsoft knows the Return on Investment (ROI) of each of its employees. Pandora knows what’s your current music mood. Amazing, isn’t it?
Call it the stereotype of mathematician nerds or the Holy Grail of predictive analysts of modern-day. Whatever you call it, Data Mining is the new gold rush for many industries.

Data Mining to Predict Customer Actions

Today, companies are mining data to predict the exact actions of their prospective customers. When a huge chunk of customer data is seen through a series of sophisticated, formatted, and collective data mining processes, it can help create future-ready content of marketing and buying messages. This diminishes the scope of errors and maximizing customer loyalty.
Also, a progressive team of coders and statisticians help push the envelope as far as the marketing and business tactics are concerned about collecting data and mining practices that are exceptional.

Data Mining for Real Estate, Retail, and Automobile Industries

Mentioned below is a detailed low-down of three industries – real estate, retail, and automobile – where LoginWorks Software has employed the most talented predictive analysts and comprehensive behavioral marketing platforms in the industry. Let’s take a look.

Data Mining for Real Estate

The real estate industry looks past the Spray-And-Pray marketing tactic by mining user data.

A supremely competitive market that is to an extent unstructured too, the real estate industry needs to reap the advantageous benefits of data mining. And, we at LoginWorks Software understand this extremely well!

Data Mining Requires a Robust Team

Our robust team of knowledge-driven analysts makes sure that we predict future trends, process the old data, and rank the areas using actionable predictive analytics techniques. By applying a long-term strategy to analyze the trend and to get hold of the influential factors that are invested in buying a property, our data warehouses excel in using classical techniques, such as Neural Network, C&R Tree, linear regression, Multilayer Perception Model, and SPSS in order to uncover the hidden knowledge.

Big Data Is the Bedrock

By using Big Data as the bedrock of our Predictive Marketing Platform, we help you zero-in on the best possible property available for your interest. Data from more than a dozen reliable national and international resources to give you the most accurate and up-to-the-minute data.

Right from extracting a refined database of one’s neighborhood insights to classic knowledge discovery of meaningful techniques, our statisticians have proven accuracy. We scientifically predict your data by:

  • Understanding powerful insights that lead to property-buying decisions.
  • Studying properties and ranking them city-wise, based on their predictability of getting sold in the future.
  • Measuring trends at the micro-level by making use of Home Price Index, Market Strength Indicator, Automated Valuation Model, and Investment Analytics.

Data Mining for the Retail Industry

Data mining to a retailer is what mining gold is to a goldsmith.

Priceless, to say the least. To understand the dynamics and suggestive patterns of customer habits, a retailer is always scouting for information to up their sales and generate future leads from existing and prospective consumers. Hence, sourcing your birth date information from your social media profiles to zooming upon your customer’s buying behavior in different seasons.

Data Mining Transforms Customer Info to Points of Sale

For a retailer, data mining helps the customer information to transform a point of sale into a detailed understanding of

(1) Customer Identification;

(2) Customer Attraction;

(3) Customer Retention; and

(4) Customer Development.

A retailer can score potential benefits by calculating the Return on Investment (ROI) of its customers by:

  • Gaining customer loyalty and long-term association;
  • Saving up on huge spend on non-targeted advertising and marketing costs;
  • Accessing customer information, which leads to directly targeting profitable customers;
  • Extending product life cycle;
  • Uncovering predictable buying patterns that lead to a decrease in spoilage, distribution costs, and holding costs.

Retail Requires Bespoke Data Mining Techniques

Our specialized marketing team targets customers for retention by applying myriad levels of data mining techniques, from both a technological and statistical perspective. We primarily make use of the ‘basket’ analysis technique that unearths links between two distinct products and ‘visual’ mining techniques that helps in discovering the power of instant visual association and buying.

Data Mining for the Automobile Industry

Often called the ‘industries of industries’, the automobile industry of today is robustly engrossed in constructing new plants and extracting more production levels from existing plants.

Like food manufacturing and drug companies, automakers are in an urgent need to build sophisticated data extraction processes to keep themselves all equipped for exuberantly expensive and reputation-damaging incidents. If data analytics by Teradata Corp, a data analytics company, is to be believed, then the “auto industry spends $45 billion to $50 billion a year on recalls and warranty claim”. A number potentially damaging for the automobile industry at-large, we reckon!

Hence, it becomes all the more imperative for an automobile company of repute to make use of the enhanced methodology of data mining algorithms.

Data Mining Helps Spout Patterns, Trends, Rules, & More

Our analysts would help you to spot insightful patterns, trends, rules, and relationships from scores and scores of information, which is otherwise next to impossible for the human eye to trace or process.

Our avant-garde technicians understand that an automotive manufacturing industry does not interact on a one-to-one basis with the end consumers on a direct basis, hence we step into the picture and use our fully-integrated data mining feature to help you with the:

  • Supply chain procedure (pre-sales and post-sales services, inventory, orders, production plan).
  • Full A-Zee marketing facts and figures(dealers, business centers, social media handling, direct marketing tactics, etc).
  • Manufacturing detailing (car configurations/packages/options codes and description).
  • Customers’ inclination information (websites web-activities)

Ready for a Change?

To wrap it all up, it is imperative to understand that the customer data is just as crucial for actionable insights as your regular listings data. Behavioral data and predictive analysis are where the real deal lies. This is true because, at the end of the day, it is all about targeting the right audience with the right context!

Move forward in your industry with LOGNWORKS SOFTWARES’ comprehensive, integrated, strategic, and sophisticated Data Mining Services.

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